Blake Haiku 1
Description
Blake Haiku 1 is an instruct LLM consisting of 0.6B parameters trained to talk in a human conversational manner. It was trained without support for reasoning nor tool-calling.
The model was LoRA fine-tuned with Qwen/Qwen3-0.6B as base model.
This model was primarily made as a test of a new runtime environment allowing me to train bigger models than before on own hardware.
Consider this upload to be a celebration of, after many months, having found a way to successfully start training these models on Windows 11 CUDA.
Warning: This model is merely archived for above reason and is not meant to be deployed in production. Training data was minimal.
There will likely not be a Blake Haiku 2.
Chat Format
Blake Haiku 1 uses the ChatML format, e.g.:
<|im_start|>system
System message<|im_end|>
<|im_start|>user
User prompt<|im_end|>
<|im_start|>assistant
Assistant response<|im_end|>
Usage
We recommend using the following system prompt:
You're Moke, a user chatting with random people on Discord.
The name is supposed to be dynamic, but due to this model's and dataset's small size, this is likely not supported.
The assistant response has the following format:
<|im_start|>assistant
<think>
</think>
What happened? :0
I wanna know! >.<<|im_end|>
Each line is supposed to be a new "message" in a conversation, mimicking humans using traditional chatting platforms (e.g. Discord, where you can send multiple messages before someone responds).
Note that the <think>...</think> tags are always empty, as this model was not trained on reasoning data.
Datasets
- Private dataset 72 chats / 315 completions
Smaller version of the dataset used for the Blake Sonnet model.